Bibliographic record
Abstract
Pierre Marie’s report on acromegaly in 1886 opened an era of interest in pituitary tumors and renewed inquiry into the function of the pituitary gland (1) . Prior to that time, abnormalities of the pituitary had been infrequently recorded. Landolt wrote that Plater in 1641 described a 24-yr-old man with progressive loss of vision, convulsions, and weakness (2) . Postmortem examination revealed a pituitary tumor the size of a hen’s egg. Rolleston in his book, The Endocrine Organs in Health and Disease (3) , noted that Bonet in 1679 and Wepfer in 1681 reported enlargement of the pituitary, Vieussens in 1705 documented enlargement of the pituitary with blindness, and Gray and Ward in 1849 each reported a tumor of the pituitary to the Pathological Society of London. Ward’s patient, a young woman who had experienced progressive loss of vision, was at postmortem found to have a large pituitary tumor also involving the infundibulum and pressing on the optic nerves (4) . Gray’s patient was a 30-yr-old woman with headaches and confusion. At postmortem examination, her pituitary was “large,” as was the sella, which contained pus, and communicated with the pharynx (5) . Earlier, in 1823, Ward published his findings in a 38-yr-old male who for 3 yr had failing vision and, in the last days
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".